A gamified system with multiple LLM agents of varied personalities gathers interaction data to produce more effective and interpretable Big Five personality assessments than single-context methods.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
LLM framework converts facial action unit sequences to text, fuses with responses, and regresses to personality scores, reporting lower errors and higher correlations than baselines on AVI-6.
citing papers explorer
-
Exploring a Gamified Personality Assessment Method through Interaction with LLM Agents Embodying Different Personalities
A gamified system with multiple LLM agents of varied personalities gathers interaction data to produce more effective and interpretable Big Five personality assessments than single-context methods.
-
LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion
LLM framework converts facial action unit sequences to text, fuses with responses, and regresses to personality scores, reporting lower errors and higher correlations than baselines on AVI-6.